Senior Analytics Engineer / BI Product Engineer

About the Role

LiftIQ is looking for a Senior Analytics Engineer / BI Product Engineer to build the

reporting and analytics products our teams use to run the business.

This is not a traditional BI role where stakeholders provide specifications and you simply

build dashboards. We need someone who can understand the underlying business

problem, determine what users actually need, and turn ambiguous requests into accurate,

actionable analytics.

Often, the best solution will be different from what was originally requested. You should be

comfortable challenging requirements, identifying insights users did not know to ask for,

and designing reports that help people make decisions - not simply giving them more data.

This is also a highly technical full-stack analytics role that blends analytics engineering

with BI product engineering. You will work across BigQuery, dbt, TypeScript, Next.js, and

React, using Claude Code extensively to accelerate development.

Data correctness is critical. Wrong numbers are worse than crashes.

You will own the accuracy, reliability, and usability of LiftIQ's reporting products

end‑to‑end - from data modeling and metric definitions to dashboard experience and

permissions.

What You'll Do

• Work directly with stakeholders to understand business questions and translate

them into useful analytics products.

• Design metrics, reports, dashboards, and visualizations that surface actionable

insights.

• Write sophisticated BigQuery SQL and build/extend dbt models,data marts and

dimensional models (facts, dimensions, semantic layers)

• Reconcile reporting against source systems and investigate data discrepancies.
• Build dashboards end-to-end across the data layer, semantic layer, application

layer, permissions, and automated tests.

• Use Claude Code heavily while maintaining ownership of the underlying

architecture, logic, and data correctness.

• Protect sensitive financial and compensation data through rigorous server-side

access controls.

• Write automated tests for metrics, business rules, and permissions.
• Document business logic, metric definitions, and data models to ensure clarity and

consistency across teams

What We're Looking For

• Essential

Exceptional SQL skills

• Deep experience with analytical SQL, including complex joins, window functions,
• attribution, aggregation, data grain, reconciliation, and performance. BigQuery experience
• is strongly preferred.
• Strong analytical and business judgment
• You can understand what decision a stakeholder is trying to make, determine which
• metrics matter, and design something more useful than simply fulfilling the original
• request.
• Strong requirements-gathering skills
• You are comfortable working directly with business users, asking the right questions,
• understanding unfamiliar processes, and turning ambiguity into a clear solution.
• dbt experience
• Experience using dbt in a high-scale production data environment. Experience with
• dimensional modeling, semantic layers, and metric governance.
• Data skepticism
• You instinctively validate, reconcile, spot-check, and investigate. You should be
• uncomfortable shipping a number you cannot explain.
• Testing discipline
• Experience building testable analytics logic and automated tests for metrics and business
• rules. Experience with version control, PR hygiene, and modular analytics engineering
• practices.
• English: strong working proficiency (B2+), with the ability to communicate directly with business stakeholders and gather requirements.

Nice to Have

• Performance or affiliate marketing experience, including CPL, CPA, EPC, ROAS, and

media-buying economics

• Experience with platforms such as Everflow, Ringba, RedTrack, Voluum,

LeadProsper, or HubSpot

• GCP / Cloud Run / Cloud Scheduler / Cloud Build
• Python ETL and API integrations
• Payroll or commission systems experience
• Claude API or other LLM application development
• Interactive data visualization
• Playwright / E2E testing

Tech Stack

Data: BigQuery, dbt, Python ETL, Google Sheets

Application: Next.js 14, TypeScript, React, Tailwind, NextAuth, Neon Postgres

AI: Claude Code, Claude API

Testing: Vitest

Infrastructure: GCP, Cloud Run, Cloud Scheduler, Cloud Build, Docker

What Success Looks Like

A strong person in this role becomes someone the business brings problems, not

dashboard specifications.

If someone says, "I need to understand why this buyer's margins dropped," you should be

able to understand the business context, interrogate the data, identify the relevant metrics

and potential causes, and build something that makes the answer clear.

You should be equally comfortable debugging a subtle SQL grain issue, talking with a

stakeholder about how their business works, and using Claude Code to turn the resulting

solution into a production dashboard.

This is a full-stack analytics role, but the hardest part of the job is data correctness,

modeling discipline, and analytical judgment - not frontend development.

Success also means stakeholders trust your numbers without hesitation, dashboards

become decision tools rather than data dumps, and metric definitions remain consistent

across teams.